JIM
Journal of Innovation Management
The International Journal on Multidisciplinary Approaches on Innovation
Volume 4 Issue 3 | open-jim.org
Table of Contents
Editorial
Revisiting Openness: A must for Society
Anne-Laure Mention, João José Pinto Ferreira, Marko Torkkeli ... 1-2
Letters
Retail Medicine in an Era of IoT and Medical Errors in the Age of Ubiquitous Connectivity
Shoumen Palit Austin Datta ... 3-6
Why the New Logics of a Connected World Affect Traditional Innovation Structures from the Bottom Up – and the Role of Open Innovation Networks & Ecosystems in Finding Proper Answers
Hannes Erler ... 7-11
Articles
The Circle of Innovation
Fred Young Phillips ... 12-31
The impact of timing in innovation management
Ronald C Beckett, Andrew O'Loughlin ... 32-64
Company Value Creation through Effective Innovation Process Management
Miroslav Špaček, Emil Vacík ... 65-78
Coopetition at Elevator Pitch Events? A Case Study of Micro-activities at a Business Innovation Event
Rauno Rusko, Katja Härkönen, Sofia Liukkonen ... 79-100
Mapping and Benchmarking Technological Innovation of Three International Petrochemical Companies
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Journal Editors
João José Pinto Ferreira Marko Torkkeli Anne-Laure Mention
Economic and Social Science Areas
Associate EditorsAlan Robinson - CREATIVITY AND IMPROVISATION
Alex Bennet - LEADERSHIP & ORGANIZATIONAL BEHAVIOUR Anette Broløs - SERVICE INNOVATION
Aurora Teixeira - INNOVATION Bruno Van Pottelsberghe - ECONOMICS Carlos Melo Brito - MARKETING David V. Gibson - INNOVATION Deák Csaba Tamás - INNOVATION Denis Dennehy - DESIGN THINKING
Faridah Djellal - INNOVATION ECONOMICS
Gabriel Amitsis - SOCIAL INNOVATION AND ENTREPRENEURSHIP Giovanni Perrone - OPEN INNOVATION
Howard Van Auken - ENTREPRENEURSHIP
Ioannis N. Katsikis - INNOVATION AND ENTREPRENEURSHIP John Lewis - LEADERSHIP & ORGANIZATIONAL BEHAVIOUR Jose-Luis Hervas-Oliver - INNOVATION ECOSYSTEMS
Maria Smirnova - MARKETING
Marina van Geenhuizen - INNOVATION Michael Dell - CONSULTING
Milton Sousa - LEADERSHIP & ORGANIZATIONAL BEHAVIOUR Pawel Kawalec - RESEARCH METHODS
Peter Prud'homme van Reine - CROSS-CULTURAL ISSUES Shawn Carraher - ENTREPRENEURSHIP
Stefano Pace - MARKETING
Susan Coleman - ENTREPRENEURSHIP Susanne Durst- KNOWLEDGE MANAGEMENT
Member of the Editorial Board
Alfredo Behrens - CROSS-CULTURAL ISSUES Bertil Hultén - MARKETING
Catarina Roseira - MARKETING Danny Soetanto - INNOVATION
Faïz Gallouj - INNOVATION ECONOMICS
Fernando Jose Garrigos Simon - STRATEGY & KNOWLEDGE MANAGEMENT Hetty van Emmerik - ENTREPRENEURSHIP
Hiroshi Tamura - MARKETING
Jose-Luis Munuera-Aleman - MARKETING Kip Becker - MARKETING
Luis Filipe Reis - MARKETING Nurul Indarti - INNOVATION
Semra Aşcıgil - ENTREPRENEURSHIP
Vincent Xiaoguang QI - CROSS-CULTURAL ISSUES Xu yang - INNOVATION
Technology and Science / Industry
Associate EditorsAntónio Augusto Fernandes - NEW PRODUCT DEVELOPMENT Arturo Molina - COLLABORATIVE NETWORKS & INTELLIGENT MANUFACTURING SYSTEMS
Carlos Bremer - VALUE CHAIN MANAGEMENT
Eng Chew - SERVICE AND BUSINESS MODEL INNOVATION / ENTERPRISE ARCHITECTURE
Engelbert Westkaemper - MANUFACTURING Eugénio Oliveira - INTELLIGENT SYSTEMS Henderik A. Proper - ENTERPRISE ENGINEERING Jim Richards - SPORTS
João Falcão e Cunha - SERVICES João Paulo Vilas-Boas - SPORTS
Joerg Schulte - OPERATIONS AND PROCESS MANAGEMENT José Manuel Mendonça - MANUFACTURING
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Juan Vicente García Manjón - INNOVATION
Lihui Wang - OPERATIONS AND PROCESS MANAGEMENT
Luis Camarinha-Matos - COLLABORATIVE NETWORKS & INTELLIGENT MANUFACTURING SYSTEMS
Mauro Rosa - ELECTRIC POWER SYSTEMS Paul P. Maglio - SERVICES
Sara de Freitas - GAMES AND ENTERTAINMENT
Ted Goranson - AGILITY, KNOWLEDGE MANAGEMENT, AND CHANGE MANAGEMENT
Thomas Østerlie - INNOVATION
Toshiya Kaihara - COLLABORATIVE NETWORKS & INTELLIGENT MANUFACTURING SYSTEMS
Urcun John Tanik - CYBER PHYSICAL SYSTEMS Vladimiro Miranda - ELECTRIC POWER SYSTEMS
Member of the Editorial Board
Abdullah Eroglu - CYBER PHYSICAL SYSTEMS Anelize Van Biljon - SERVICES
António Lobo Ribeiro - OPTOELECTRONICS Casper Harteveld - GAMES AND ENTERTAINMENT Claudio Pinhanez - SERVICES
Eberhard Bessey - MANUFACTURING
Giacomo Copani - OPERATIONS AND PROCESS MANAGEMENT Hélio Roesler - SPORTS
Hisham El-Shishiny - SERVICES João M. Sousa - OPTOELECTRONICS
José António Faria - OPERATIONS AND PROCESS MANAGEMENT Jose Arturo Garza-Reyes - OPERATIONS AND PROCESS MANAGEMENT Júlio Cerca Serrão - SPORTS
Kiili Kristian - GAMES AND ENTERTAINMENT
Myrna Fatima Flores Pineda - COLLABORATIVE NETWORKS & INTELLIGENT MANUFACTURING SYSTEMS
Ovidiu Noran - COLLABORATIVE NETWORKS & INTELLIGENT MANUFACTURING SYSTEMS
Editorial
Revisiting Openness: A must for Society
Anne-Laure Mention1, João José Pinto Ferreira2, Marko Torkkeli3
1Luxembourg Institute of Science and Technology, Visiting Professor & Deputy Director of Centre d'étude de la Performance des Entreprises University of Liège; 2INESC TEC - INESC Technology and Science and FEUP - Faculty of Engineering, University of Porto, Portugal;
3Lappeenranta University of Technology, Finland; anne-laure.mention@list.lu, jjpf@fe.up.pt,
marko.torkkeli@lut.fi
Academic literature increasingly stresses the predominance of openness in contemporary organizations - porous boundaries, virtual and agile teams, temporary hierarchies, interconnectedness of networks and ecosystems. Managerial literature also abundantly depicts the benefits of openness. In contrast to what is being observed and reported at organization level, Western Societies and some of their elected leaders currently advocate closeness: protecting borders, erecting walls and barriers, either physical, administrative or legal. This paradox raises concerns: how can individuals and firms be and remain open, while nations isolate and seclude? How can we build an inclusive society while rejecting differences? How can we achieve innovation when turning our backs to variety and diversity?
The very cradle of European ideals, among others the freedom of movement of people and capital, is facing an incredible push backwards, with the tightening of its regulations and the implementation of stricter rules and policies with regard to immigration. Former Eastern European countries, which have been benefitting for about a generation – since the fall of the Berlin Wall in 1989 – are also closing up and self-centring.
Maybe we should go down to the basics! We all live and die, but we seldom reflect upon our existence. What is life? The songs from the musical “Zorba the Greek” give us some answers, namely “Life is…“ and "The First Time". They talk about feelings and emotions, and they talk about all those things that make our hearts both beat and melt.
In a previous editorial, we discussed Openness, however, and as we see societies around the world building new barriers to protect their citizens against the unknown, the whole world should probably go through some in-depth reflection. Anyone remembers the first picture of Planet Earth taken from outer space? Did anyone realize we are all in there together? As Carl Sagan once put it “Look again at that dot. That's here. That's home. That's us.”
So, what is happening? This unprecedented shift towards closeness in Western societies clashes with the growing appetite for openness in other parts of the world, where policies and practices towards openness thrive. Asian countries build alliances, open up their markets, and initiate free trade agreements; and source ideas, expertise,
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novelties and potential, drain more and more brains and hands so as to support their booming economies.
Could the Maslow Hierarchy of Needs help the mechanics of these trends? It would likely help. It is likely that people and societies from all walks to life, may be feeling a threat to their fundamental cultural component. On the other hand, safety needs such as job security, protection from harm and the avoidance of risk, are likely to be in people’s minds. So, where is the solution, how can people in desperate need be helped and supported, while ensuring that everyone feels considered, respected and with the confirmed feeling that their needs are being properly considered.
Special care should be taken in the careful reconsideration of the notion of openness at a political and societal level in Western societies, so as to avoid the expectable negative consequences of isolation and of the extremes, whichever those are. A reconsideration that must be meaningful for Society as a whole. Participative revisiting of openness through a collective engagement of all stakeholders and the redefinition of common values is not optional, it is a must for so-called modern societies. Both life and society need proper innovation management framework – preferably more open one!
Innovatively Yours,
Anne-Laure Mention, João José Pinto Ferreira, Marko Torkkeli Editors
Retail Medicine in an Era of IoT and Medical Errors in
the Age of Ubiquitous Connectivity
Dr Shoumen Palit Austin Datta MIT Auto-ID Labs
Research Affiliate, Department of Mechanical Engineering, MIT
shoumen@mit.edu
Letter from Academia
Digital diffusion in healthcare is poised to usher delivery of care in integration with software as a service to the edge. Time compression due to the latter may catalyze the convergence between "sense and response" in a manner which may enhance quality of service (QoS) or quality of care at the point of contact (PoC). Digital transformation is likely to influence the broad spectrum of instances ranging from high acuity patients to preventive care scenarios. Access to healthcare for individuals before they become patients may eventually lead to improved health and reduced healthcare cost.
1
Introduction
The deaths due to medical errors (Figure 1) in the US are, in part, due to greed. It stems from the mantra of maximum profit optimization which is the daily chant of vendors in the health industry in the US. In an age where ubiquitous connectivity can be a part of our daily regimen, the resistance to medical device interoperability1 is a cold blooded strategy exercised by the medical industry to build walls around “their” medical devices and data to prevent the collective view, analysis and shared use of distributed information access which may reduce medical errors. The laissez-faire US policies empowers these egregious errors and Wall Street rewards the practitioners of this epic evil in unhealthy proportions.
1http://www.mdpnp.org/ Accessed November 2016
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Fig. 1. Most common causes of death in the United States, 2013 (Martin and Michael 2016)
Decentralization of this epic evil control with secure open data (EHR, EMR) and a new breed of medical device manufacturers promoting interoperability by design, may be one solution. A choke point is the lack of infrastructure required for semantic interoperability between systems which uses different standards. Thus, interoperability between standards is equally critical but one which the behemoths may vociferously resist to protect their turf.
2
Elusive Quest for New Roads
Over the past half century, the principles of ubiquitous computing has percolated down to the practice of ubiquitous connectivity. One manifestation is the concept of the networked physical world which led to a range of ideas commonly referred to as the internet of things.
IoT is a design metaphor and the quintessential infrastructure for digital convergence by design. It is in this domain that we may seek conceptual resolution of some of the problems in health IT. But, IoT is not a panacea for health and healthcare. It will not resolve all the ills and chronic malfunctions in the medical industry unless the human roadblocks are dead.
“Eine neue wissenschaftliche Wahrheit pflegt sich nicht in der Weise durchzusetzen, dass ihre Gegner überzeugt werden und sich als belehrt erklären, sondern vielmehr dadurch, dass die Gegner allmählich aussterben und dass die heranwachsende Generation von vornherein mit
der Wahrheit vertraut gemacht ist.” (Max Planck) (Wikiquote, 2016). [A new scientific truth does not, generally speaking, succeed because the opponents are convinced or declare themselves educated, however because they die and the new generations from the beginning learn about it as the truth.]
IoT is poised to re-invent almost every facet of health and non-emergency healthcare based on ubiquitous connectivity between in vivo precision metabolomics and the need for an environment fostering wellness, preventive medicine or collective clinical attention/action.
The tsunami of the principles and practice of connectivity is expected to usher in an unprecedented era of healthcare information technology that shall be woven into the daily fabric of our lives almost through our entire life-cycle, from conception to the grave.
Digital by design is the fabric that businesses may use in an era where IoT may be the predominant design metaphor. As a part of the group that catalyzed connectivity and ushered in the current networked society, one must plan to help the growth of digital entrepreneurship and intrapreneurship to lift many boats, not just a few yachts. Trans-disciplinary convergence of medicine and engineering offers to morph the brick and mortar clinic/pharmacy from its emergency/retail outlet concept to be an integral function at home for health and healthcare with decreasing demand for high acuity units (HAU).
Retail clinics and “pharmacies” will undergo transformation to create the 22nd Century service centers for medicine, perhaps something akin to “Jiffy Lube” (Boots, Walgreens, CVS) rather than a visit to Sears Auto Center (MGH). The transformation will be catalyzed by pioneers who will usher in, albeit in phases, convergence of a wide variety of precision medicine tools applicable on a massive scale and harvest metabolomics data from device-agnostic, protocol-agnostic, platform aggregators which will connect to streaming data inside and outside the body (humans, animals). Predictive analytics from person-specific data will be the digital path for precision clinical “sense and response” system and offer prescriptive analytics. It will serve almost all facets of preventive medicine, non-emergency medicine but may exclude sudden extreme trauma and few selected ambulatory scenarios.
Retail healthcare may serve as the future point of contact for the confluence of preventive medicine, precision medicine, primary care, tele-health and remote diagnostics. Retail health industry must reform their mission from selling drugs to acquiring data, analyzing and advocating in addition to building alliances to serve individuals who are not patients. The potential of digital by design health IoT will generate business growth and generate massive revenue through pay-per-use
micro-revenue schemes. It may help those in the US who are less2 fortunate and reduce the
barrier to entry even for markets in L-26 countries3 where health spending is less than
2http://www.irp.wisc.edu/publications/focus/pdfs/foc262l.pdf (Accessed November 2016)
3http://www.who.int/healthsystems/topics/financing/healthreport/41FiscalSpace.pdf (Accessed November 2016)
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$50 pa for 2+ billion people (www.pih.org).
Imagination, invention and innovation must be coupled with wireless telecommunication based remote monitoring where changes in physiological status or alerts could trigger applications via intelligent agents using functional mesh (networks) for multi-directional multi-cast communication of data, information, analytics, intelligence and streams for real time decision support or at-home care or ambulatory access depending on the "sense and response" system of systems that provide one-on-one guidance at point of contact (POC).
The retail health industry must demonstrate this concept on a large scale for credibility. It must create the local and global ecosystem of competencies necessary to provide the end to end value chain. It must be driven by less greed and more pay per service. Cybersecurity4, trust, authorization, validation, privacy, policy, regulatory compliance and authentication may require digital ledgers, such as blockchain-like concepts, to track, trace and secure every instance and events related to every process and nested sub-processes.
3
Conclusion
The complexity calls for a global surge of and focus on, collective entrepreneurial as well as intra-preneurial recombinant innovation. It will create new lines of business and immense economic growth but not through traditional channels and existing business models or organizational status quo. This calls for a new organizational platform approach where credible groups lead and coalesce tools from a diverse array of providers and champion a new form of delivery.The leadership must embody the relentless pursuit of frontiers without the fear of failure to lift the future plight of humanity through distributed medical care beyond boundaries and definitions. One must continuously re-invent to re-align with new research, new inventions, new theories, new ideas, new science, new ways to help people and customers, locally and globally. If one thinks that any one solution or company or provider or nation holds the key then one may be suffering from that impossibly incurable ailment commonly referred to (in the medical jargon) as solipsistic bliss.
4
References
Makary M. A, Michael, D. (2016). Medical error—the third leading cause of death in the US BMJ; 353 doi: http://dx.doi.org/10.1136/bmj.i2139.
Wikiquote (2016) Accessed November 2016.
https://de.wikiquote.org/wiki/Max_Planck.
Why the New Logics of a Connected World Affect
Traditional Innovation Structures from the Bottom Up –
and the Role of Open Innovation Networks & Ecosystems
in Finding Proper Answers
Hannes Erler
Director Open Innovation Networks at Swarovski KG.
hannes.erler@swarovski.com
Letter from the Industry
2016 has brought us new learnings about ecosystem dynamics and the transformation of design thinking and agile development methods. What most of these methods have in common is a divergent and a convergent phase that allows to think boldly and broadly on the one hand, and to recognize priorities and enable speed on the other hand. But industry logics are very different from theoretical settings as there are complex organizational factors at play which encompass diverse cultural and sub-cultural behaviors. The challenge for the young Swarovski Open Innovation Networks approach is to find ways to manage diversified networks of connections which blur boundaries, collaboration, and interdependence, thus characterizing the real logics of modern innovation ecosystems. The tremendous potential that has been recognized and captured from different R&D efforts of big industry players and research institutes through structured Open Innovation efforts - and how this new value may be transformed into the company’s markets - is the central topic of this article.
1
The new ecosystem dynamics
Shortened life cycles of products, speed of technological change and omnipresent availability of information threaten every organization these days. In the area of Innovation Management the year 2016 has brought us a lot of new answers, methods and good practices. But was there any new revolutionary learning? When I met Prof. Bob Cooper, the inventor of Stage Gate, while presenting at the 2016 Stage Gate Summit, he mentioned the transformation of agile methods, such as Scrum and Sprint, proven principles in area of software development, into the area of physical product innovation. In his opinion probably one of the biggest opportunities to increase speed and drive of physical product innovation, and one of the biggest moves since the introduction of Stage Gate logics in the 1990’s. A few months later I met Prof. Henry Chesbrough, known for his work on Open Innovation, in Porto at the EU OI-Net conference. He very much focused on understanding the deep societal change of our days and how to find purpose and meaning for innovating in new eco system environments.
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Thinking, the Lean Start up Model from Eric Ries, the Business Model Canvas from Prof. Oliver Gassmann or “Jobs to be Done” from Clayton Christensen.
When we deeper look into them we find out that industrial experiences have been providing data and management learning, and academics have derived their theories around these success stories and stories of failure, and vice versa. This circle of empirical and theoretical management learning is very important in order to develop new solutions and answers. But industry logics are very different from theoretical ideal settings because they have at times hundreds of people in different organizational settings, encompassing diverse cultural and sub-cultural behaviors. And that's the reason why these processes cannot simply be transferred 1:1 into an organization. As practitioners we are forced to choose and train the right methods for the right challenge. The more we go beyond our core businesses towards adjacent and transformative innovation we see that the clever orchestration of methods begs a deeper understanding. What they all have in common is a divergent and a convergent phase that allows to think boldly on the one hand, and to recognize priorities and enable speed on the other hand.
We create environments where all these new methods and dynamics are positioned as drivers in innovation ecosystems. Diversified networks of connections, blurring boundaries, collaboration, and interdependence characterize the logics of ecosystems. Innovation ecosystems in most cases consist of a science ecosystem, producing knowledge and technologies in an exploratory behavior mode and a business ecosystem, producing value for customers and companies in an exploitative mode. The definition of ecosystems is coming from the natural world: communities of living organisms interacting within their shared environment, simultaneously competing and collaborating, creating and sharing resources, and adapting together in the face of inevitable external disruptions. The look into these solutions coming from natural systems can provide us with helpful insights as to how innovation could be understood.
2
Changing dynamics
As a company we have experimented with many of the mentioned processes with different success and outcome. We were a quasi-monopolist of the classical crystal business up till 2008 when we suddenly faced an explosion of competition. The need for more agile processes, robust strategies and new technologies was obvious. After the definition of innovation search fields and must-win battle fields, we saw that we had to significantly open up our mindset and orientation towards the outside world.
Based on both our long tradition of incorporating technologies from other industries into the world of fashion and design, and on the founder’s spirit - who recognized very early in the 20th century that “development never stands still and that an invention in one field inevitably leads to inventions in another fields” - we decided, among other changes, to allocate dedicated resources to the field of Open Innovation and inter-organizational networking.
3
The foundation of OI Networks
The Open Innovation Networks department was officially established in 2013 in order to implement a foundation for strategic alliances and initiatives with focus on outside-in technical outside-innovation and long-term relationships leadoutside-ing to additional busoutside-iness for both sides.
Our initial mandate was to formally build a network of potential partners who could contribute to any of our innovation categories, with a focus upon outside-in breakthrough technologies for our business-driven search fields, while increasing transparency and culture of openness and trust for all innovation activities both internally and externally. Initially our key stakeholders included all research, innovation and design related internal actors, those responsible for budget & prioritization per innovation category, as well as various internal leading experts, innovators, and department heads depending on the topic or field. Finally, we established an engagement process which tracks all potential partners through our defined stages of engagement. Conclusively, we established a system comparable to the lead generation or conversion process common to traditional sales & marketing functions, and customized a customer relationship management as software support system. With this implementation, our Open Innovation network became an asset in and of itself, allowing for sustainable operation and transparent collaboration, while generating value for multiple business units, reaching far beyond our initial key stakeholders, and providing interested employees access to the data and networking communities that we manage within our portfolio.
4
Creating customer value through open innovation networks
In November 2015, we were awarded with the “Open Innovation Award” from the Zeppelin University in Germany in the category “Best Open Innovation Network”. This helped us a lot in trusting our interpretation of how we see innovation working in future. Involving external partners was not something new for Swarovski, but to do this on different levels of the organization and to integrate such collaboration into our day-to-day work required - and still requires - both a change in mindset as well as acquiring new skill sets.
We very soon realized the tremendous potential in transforming the results from different R&D efforts of big industry players and research institutes into our markets. However, externally we were not perceived as a technology-oriented company and we have not been present in the global science ecosystems. Three years later, we have now spoken with over hundreds of companies, mainly cross industry, and developed a few dozen opportunities based upon new technology integrations. The analysis of our partner pipe-line surprisingly showed us that their research labs operate in 33 different countries worldwide.
The main source of new contacts was realized through speaker invitations and participation at over two dozen global conferences and networking events. Other indirect sources included referrals from existing partners, or recommendations from networking intermediaries. This widened the ability of the organization to integrate
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external knowledge in a fast and seamless manner, delivering on our promise to provide access to breakthrough innovation and increased development speed from idea to market.
5
Arriving in the new innovation ecosystems
As with many businesses, we are evolving from traditionally providing our customers with new products to transforming our offers into new comprehensive solutions. That means that the ability to efficiently collaborate with external science ecosystems – openly, quickly, and more often than in the past – is even more crucial.
The industries we serve simply do not allow the time to follow linear development models that require years to make a new technology available for the markets. Rather we see processes that start in corporate laboratories and research institutes very early on, which are then quickly transformed into new product and service concepts by directly involving the customer at the very beginning. Collectively, these participants comprise as what we refer to as the innovation ecosystem, integrating the science and business ecosystems together as shown in the graphic below. Entitled “The Logics of Innovation Ecosystems,” we depict a holistic view of our ecosystem-based approach, a hybrid of the models from Gene Slowinski (Rutgers University) and Katri Valkokari (VTT) in combination with the methodologies we rely upon throughout the various phases of networked innovation development.
6
Our biggest learnings from our open innovation journey
Another shift that we observe in industries today is the so-called “Fail Fast - Learn Fast” and “Experimentation” culture. This is something we can particularly observe in start-up environments, however this has now also risen to the top of the innovation agendas for large corporate environments as well. Our company recently launched a private equity partnership with the community, leveraging the collaborative networking and experimental spirit that the company has been known for since its founding.
Coming back to the previously mentioned agile methods, we see a big focus on design thinking and sprint methods along with a redefinition of the places where - and the processes how - we innovate.
We know exactly how all these methods work, what benefit they can bring at what phase of the innovation development process, and how they can be used. However, in big organizations they must also be combined with the principles of systematic organizational development.
Schumpeter’s theory on creative destruction then gains new meaning and can be seen as a company asset if your employees are encouraged to adopt these new methods of thinking. There are a few companies showing us how creative destruction can be embraced within a corporation, such as Google, Johnson & Johnson, IBM, and P&G. Open innovation then becomes a foundational cultural mindset and behavior, and not a responsibility of a single department.
We want to be the missing link between the tech and fashion industries, we therefore have to develop new practices in combining data-driven systems and design thinking methods. We believe that values along the levels of customers, organizations, ecosystems and society are the common language that determines the likelihood of success. The better the contribution to these four levels and the meaning of our products and services, the better our footprint on society as a whole will be.
With the role of Open Innovation networks we have shown only one facet of Swarovski’s innovation ecosystems. As innovation leader in our industry we have to guarantee the relevance of our technological expertise, our capabilities around inventiveness, and the ingenuity and motivation to further develop the Swarovski DNA of innovation for the next 120 years to come.
Journal of Innovation Management Phillips JIM 4, 3 (2016) 12-31 HANDLE: http://hdl.handle.net/10216/86100 ISSN 2183-0606 http://www.open-jim.org http://creativecommons.org/licenses/by/3.0 12
The Circle of Innovation
Fred Young Phillips
Yuan Ze University, Taiwan and Stony Brook University, USA fphillips@saturn.yzu.edu.tw
Abstract. Traditional models of innovation are predominantly linear, featuring
only very limited feedback loops. This paper builds on a high-level cycle of feedback between technical innovation and social change. In this grand cycle, technological innovation brings about new products but also new ways of using products and services. These in turn change our organizations and social interactions. The new structures generate new unfilled needs, spurring still more technological innovation. The Circle of Innovation is a simple idea. Yet its implications for companies and for researchers have remained unexplored. This paper discusses the Circle of Innovation’s implications. We find the Circle of Innovation (i) implies a new way to classify innovations; (ii) should change how firms assess innovations; (iii) gives a new view of target marketing; and (iv) has implications for sustainable product planning. We conclude in a more conjectural vein that the Circle of Innovation provides a frame for other nonlinear innovation models.
Keywords. Innovation; Social Change; Product Line Planning; New Product
Development; Technology Assessment; Creative Destruction.
1
Introduction: Feedback in the innovation process
Traditional models of innovation and its diffusion are predominantly linear and uni-directional, offering feedback loops only in the form of customer satisfaction measures, imitation behavior, or concurrent engineering. This paper discusses a high-level cycle of feedback between technical innovation and social change, enabling connection with newer, more detailed nonlinear models of innovation, and encouraging further nonlinear modeling and analysis.
In the proposed grand cycle, technological innovation brings about not just new products and services, but new ways of producing and using products and services. These in turn lead to new ways to interact and organize, socially and professionally. The new structures generate new unfilled needs, which are opportunities for still more technological innovation. That is, each time technology solves a problem, it generates new ones, in a continuing cycle.
The term “high-level cycle” reflects Schumpeter’s macroeconomic orientation as he set forth his seminal view of the loop between innovation and socio-economic change. The present paper ties this macro idea, recounted in Section 3 below, to management ideas that span the meso and micro levels.
The Circle of Innovation is a simple idea. Yet it:
I. Implies an additional way to classify innovations, namely, those that are new ways of satisfying old wants, and those that satisfy new, unprecedented wants;
II. Gives a new view of target marketing – a kind of uncertainty principle for innovation, in which we understand that products cannot be aimed at a usage situation, but rather, that the product changes the situation; and
III. Has implications for sustainable product line planning. The Circle implies firms should assess their own innovative products, predicting what new wants they will generate, in order to be first to satisfy them.
The paper discusses these implications. The grand cycle of socio-technical change means we should augment our thinking about innovation diffusion by considering innovation reinforcement, or a Circle of Innovation. We find that Apple appears closest among today’s companies to using the Circle of Innovation as basis for a management strategy.
After introducing the Circle of Innovation and some examples of it, this conceptual paper draws on disparate literatures to analyze the circular innovation phenomenon, and proceeds to explore each of the implications numbered above. It concludes by summarizing the findings and (in a somewhat more conjectural vein) diagramming their relation to sustainable product line planning.
This explication of the Circle of Innovation will add value to the practical and theoretical discussion of innovation.
2
Linear and nonlinear innovation models
Table 1 summarizes the traditional linear models of innovation and its diffusion. (See e.g., Godin 2005.) In these models, feedback is gained only via customer satisfaction measures; imitation behavior (Rogers, 1962; Bass, 1969); or “cyclic innovation” (Van der Duin and Hermeler, 2014) and concurrent engineering. Practically speaking, we know there are even more feedback mechanisms than this: Examples include Yelp, TripAdvisor, and Twitter reviews. Yet these are just “small” feedback loops, linking some of the detailed steps in the innovation cycle of Figure 1.
Table 1. Traditional linear models of innovation
Traditional Model 1 Scientific breakthrough ê Technological development ê Product development Traditional Model 2 Product introduction ê Customer adoption ê
Growth, maturity, decline
In contrast, this paper re-introduces a high-level cycle of feedback (Figure 1) between technical innovation and social change. Its specific contributions relative to prior literature are its focus on private-sector implications, in particular for product line (as opposed to product) planning; its presentation of a new and challenging view of target marketing; and its clarification of the benefits of comprehending the entire Circle, as
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opposed to the restricted arcs dealt with by most research on technology management and diffusion.
The Circle of Innovation enables connection with nonlinear models of innovation, e.g., National/Regional Innovation Systems (Lundvall, 2007), Triple Helix (Leydesdorff and Etzkowitz, 1996; Dolfsma and Leydesdorff, 2009; Ivanova and Leydesdorff, 2014), and “technological transitions” (Geels, 2005).
3
A brief history of the idea
Historians concerned with technology (e.g., Lipsey 2002) have noted that productivity-enhancing technical advances enable specialization – which is a kind of organizational change. For example, the plow increased agricultural productivity, enabling family or community members to spend time on supplementary pursuits, including commerce. They then, naturally (though this is not made explicit in the technology history literature) sought better ways to conduct commerce. Further innovations provided the sought-after improvements.
Fig. 1. Technological innovation self-reinforces via socio-economic change.
The foundational advance on the closed loop of demand and innovation is this famous but testy passage of Schumpeter’s (1943):
…in dealing with capitalism we are dealing with an evolutionary process. It may seem strange that anyone can fail to see so obvious a fact which moreover was long ago emphasized by Karl Marx. Yet that fragmentary analysis which yields the bulk of our propositions about the functioning of modern capitalism persistently neglects it….
Technological innovation
New ways to organize (public & private)
New ways of producing and using products & services
New products & services New problems, needs, desires & dreams New ways to interact socially
Capitalism, then, is by nature a form or method of economic change and not only never is but never can be stationary. And this evolutionary character of the capitalist process is not merely due to the fact that economic life goes on in a social and natural environment which changes and by its change alters the data of economic action; this fact is important and these changes (wars, revolutions and so on) often condition industrial change, but they are not its prime movers. Nor is this evolutionary character due to a quasi-automatic increase in population and capital or to the vagaries of monetary systems of which exactly the same thing holds true. The fundamental impulse that sets and keeps the capitalist engine in motion comes from the new consumers’ goods, the new methods of production or transportation, the new markets, the new forms of industrial organization that capitalist enterprise creates.
The passage is rich with implication. Schumpeter considers it “obvious” that capitalism is evolutionary. Evolution (of the Darwinian sort1) requires feedback between organism and environment, a non-linearity. Though he criticizes economic analyses which ignore this reality, linear models have dominated in academic economics to the present day. Economists’ overarching principle, say Atkinson and Lind (2013), has been “maximize efficiency.” But “the goal of economic policy should not be to maximize static efficiency (the ‘right’ allocation of widgets), but to create inefficiency – in the sense of disruptive innovation that makes widgets worthless.” Flichy (2008), noting that “economists usually exclude [technology] from their field of interest,” said plainly, “The linear science-technology-use schema no longer works today.” Schumpeter (1943) shared the sentiment: “A system which is efficient in the static sense at every point in time can be inferior to a system which is never efficient in this sense, because the reason for its static inefficiency can be the driver for its long-term performance.”
Schumpeter draws the feedback loop between the economy and its environment, and moreover states the “fundamental impulse” driving this interaction is technological and organizational innovation.
Ironically – as he commenced his chapter by citing Marx, whose ideas gave rise to the biggest ideological rift of modern times – Schumpeter did not credit ideology as a co-driver of social change. (Doubly ironic, really, as Schumpeter was berating other economists for ignoring the obvious.) That task fell to George Kozmetsky, an American son of Russian refugees, whose writings emphasized technology and ideology as dual drivers of change (Walters 2003; Phillips 2005; Secrest, Gibson and Butler 2011). In the model of Figure 1, ideology is subsumed under “new problems, desires, and dreams.”
Schumpeter’s chapter provides depth and theoretical substance to the casual observation of later writers (e.g., Learner and Phillips 1993; Kelly 2016) that new technologies solve today’s problems and create tomorrow’s. However, Schumpeter offered no advice of specific use to managers.
1
Elsewhere in his chapter, Schumpeter actually apologizes for resorting to a biological analogy.
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Subsequent writers attended to specific arcs of the circle of innovation. Best known is Rogers’ (1962) work on the diffusion of innovation to individuals and classes of individuals. Powell et al (1996) and Strang and Soule (1998) looked at diffusion to and across organizations.
Lounsbury and Crumley (2007) continued the latter thread, adding elements of complexity and nonlinearity. The recent growth of complexity science (see e.g., Mitchell 2009) had encouraged researchers to look for and model feedback loops in the innovation process. Geels (2005), for example, pioneered a widely cited thread of “transition” studies, showing how changing technologies and public attitudes cause a shift from one “technological regime” or dominant design to another. Rothwell (1994) showed how “generations” of innovation models have shifted over the years toward greater acknowledgment of interaction loops. However, Rothwell focused his own work on “innovation activity of firms under different socioeconomic and political circumstances” (Kotsemir and Meissner, 2013) without making contact with the wider innovation environment. Indeed, Kotsemir and Meissner note Rothwell’s later generations showed a shift from meso- to micro-level.
Most technology and innovation management (TIM) literature addresses only the first link in the Circle of Innovation: Laboratory invention to new product. A few works have addressed two links; for example, Markus and Robey (1988) look at how information technology produces organizational change. Kash (1989) attacked the broadest arc of the circle, documenting how innovations in many technological fields change organizations. Rycroft and Kash (1999) extended this work, delving more deeply into complexity considerations. Yet the loop remained unclosed: These authors did not go on to note that new organizational forms give rise to new needs which must be satisfied by further innovation.
Storytellers know how technological advances change social relations, creating new problems.
A 2008 Tony winner for Best Revival, the swinging '60s farce Boeing Boeing… follows an American lothario living in Paris who's secretly engaged to three different flight attendants. But when the new, faster Boeing jet goes into service, the ladies' schedules get jumbled, and things turn turbulent as all three of them descend on his apartment at the same time, along with an old schoolmate who can't seem to keep his pal's cover stories straight.2
Concepts suggesting the Circle of Innovation are also mentioned in passing in the “Science, Technology, and Society” sub-discipline of the sociology of science (e.g. Bijker and Law, 1992; Pool, 1999). However, neither the entertainers, the economists, the science historians, nor the STS scholars seem concerned with commerce, or the implications of the Circle of Innovation for companies.
We do not find prior TIM literature addressing the entire Circle. We surmise this is because the professional interest of most commentators is limited either to the right side or the left side of Figure 1, rather than to the entire loop. One exception, the “constructive technology assessment” thread (Schot and Rip, 1997), laid out implications for governments only, and made no prescriptions for firms.
4
Research gaps
This history shows that the cited studies illuminated important parts of Schumpeter’s loop, but collectively did not fill in all the loop’s segments nor turn the loop into a useful management tool. Schumpeter perceived the circular path between technological change and what he called economic change. His nonlinear formulation was ignored by subsequent generations of economists, who cleaved to linear models with computable equilibria. His work presented guidelines for managers only by broadest implication, without explication.
Market research was long considered (by marketers – see Kotler 2009) to be the feedback mechanism that made capitalism work. Because in the case of advanced technology products customers do not know what they want, Sony and Apple, among others, famously eschewed consumer surveys in favor of launching visionary products to the market, and were successful in doing so.
Although Rogers' (1962) diffusion model does include some "loops, short-cuts or interruptions" (Prager and Posthumus, 2010), the model begins with the innovator segment exhibiting “latent demand” for the innovation, with no identification of the source of this latent demand. The Circle of Innovation enables us to see its source: New needs emerging from new organizational forms, from new social interactions, and from
new ways of using old products and services.3
Remaining gaps include:
• No consensus emerged concerning the variables that intervene between socioeconomic change and technical change.
• Connections among any intervening variables were not closely examined. • The studies failed to see the whole circle, examining only small arcs of the
circle, and/or only specific nonlinear epicycles.
• The research focus was intra- or inter-organizational only, or reflected high-level economic thinking without reference to managerial realities or to the interactions of different sectors of society.
This paper will suggest ways to fill these gaps.
3 Rogers’ extensive work with rural populations suggests that some of the latent demand he mentions could stem simply from his informants’ poverty, a source different from the one we propose here. If one defines economic demand as need plus the ability to pay, even conscious need combined with inability to pay would comprise a demand that remains latent.
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5
The Circle of Innovation introduced
Figure 1 shows the cycle of innovation and change, from lab to society and back again. Technological change leads to new products and services, which in turn change the way we use products and services. These new usage modalities require changes in the way we organize our firms and institutions. New ways of organizing create new needs, generating demands for still newer technological fixes, and the cycle repeats.
5.1 Elements of the Circle
Schumpeter’s loop could reasonably be sliced into three arcs – Technology, Individuals, and Organizations, with innovations and their impacts flowing from T to I to O and back to T. These nomenclatures would be too abstract for the purpose of the present paper, which is to establish elements of the circle of innovation that encourage further research and compel managers’ attention. An examination of the literature cited above, filtered through the authors’ thirty years experience in technology management, suggests the six arcs (or elements) labeled in Figure 1.
5.2 Establishing the flow between successive elements
Some of the pairwise flows are backed by literature. Others are justified below by means of examples, including a running example of ORCID identifiers for researchers. The examples are chosen for illustrative impact, but readers will discern they are far from unique – in fact, in many cases they are driving forces.
Technological innovation è New products and service. This link is extensively dealt
with in the New Product Development and Diffusion of Innovation literatures.
New products and services è New ways of using products and services. Little research
has addressed this link, perhaps because it is so self-evident. Cloud computing changes the way we use computers to manage our work files. Inter alia, we no longer have to worry about version control on multiple devices, and have no need to tote files on USB keys. Other examples include E-commerce and home delivery drones, which change the ways we use retail services: We shop from our desktops, and return merchandise at the post office, not at the store. Mobile apps for bus schedules and taxi booking change the ways we use transportation services, allowing us to spend less time waiting for a bus or cab. The interactive web has completely changed the way we consume media.
New ways of using products and services è New ways of interacting socially and professionally. Two words suffice to establish this link: Facebook and Linkedin. And
not just in cyberspace: “Cars are becoming tantamount to computing devices that have as much to do with software as they do with chrome. This is changing how consumers and urban planners imagine transportation systems” (Tett, 2015).
New ways of interacting è New ways of organizing. Information and communication
technology (ICT) allowed more frequent and better-documented exchanges between industrial suppliers and customers. As a result, transactional relationships evolved into alliances. Companies now employ alliance managers. When technological change is slow – to look at another example – companies can organize in silos, each division comfortable in its niche. “At Apple, by contrast, Steve Jobs would not let divisions have their own P&Ls and demanded that his managers collaborate with other teams”
(Tett, 2015), allowing Apple to own the mobile music market, beating Sony which was less quick to re-organize. A third and more extreme example is Enron. Riding a wave of new financial instruments and an ideology of deregulation, the energy trading company created new organizational forms, including drastic decentralization (really a complete abdication of management control) and off-balance-sheet LLCs, before its demise and bankruptcy.
New ways of organizing è New needs and desires. The contractor and entrepreneurial
economies, tele-work, and the proliferation of types of laptop, handheld, and wearable computation/communication devices together illustrate this link of the Circle. They generated a need for secure BYOD (“bring your own device”) technology enabling mobile employees and contractors to access company documents while on the go. They generated a need for co-working spaces with amenities for independent workers.
New needs and desires è Further technological innovation. The classical technology
substitution theory allows for technological substitution at the end phases of the life cycle, but assumes the substituting technology provides the same user benefits as the senescent technology. What is proposed here is that social changes generate demand for new and different benefits, of kinds that were not provided by any existing technologies. These benefits may be sought and satisfied without regard to the life cycle stage of any existing technology. Kelly (2016) refers to “the never-ending discontentment that technology brings. We are… busy making up new itches that we have to scratch, creating new desires we’ve never had before.” Mead (2105) writes, “Birkenstocks, like an iPad, or an eight-dollar bottle of cold-pressed juice, are the covetable answer to a need that hadn’t existed before they came along.” More examples appear in the next section.
6
The Circle of Innovation: Further examples
Table 2 offers diverse examples of innovations making impacts that propagated around the entire Circle of Innovation. It notes, e.g., that Lyft and Uber allow drivers to rate customers online, and vice versa. Drivers use their spare time to earn by taxiing customers, and better customers get better service. Both lose time that could be devoted
to unmonitored leisure (Manjoo, 2015).4 The Table indicates some people take refuge
in retro technologies in order to escape the demands of today’s communication devices. Others (Dishman, 2016) use even newer tech (Basecamp, or Slack) for this purpose. Research into better electrical batteries has been continual over the decades, but smartphones and electric vehicles have elevated the urgency of further advances in this field. The autonomous vehicle problem is self-explanatory. We will expand on the statin drug situation in a following section, after we highlight additional examples of the Circle of Innovation.
4 By the same token, consumers’ growing awareness that their every move is monitored and evaluated signals the death of recreational shopping.
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Table 2. Circle of Innovation, short examples
Innovator Innovation Social / Organizational change
New
problems/demands Newer or prospective scientific/technological solutions
Uber, Lyft Mobile web
ride service Customers with high ratings get better service.
Desire to rest or consume without worrying about being rated or scored.
Business models in which customers are not rated. Consumers return to analog tech disconnected from social media (Sarpong et al 2016).
Astra-Zeneca,
Pfizer, Merck Statin drugs for serum cholesterol control Widely used; fewer heart-attack deaths
Side effects include obesity, cancer, diabetes.
Alternative theories of functions and effects of cholesterol in the body. Google, others Self-driving
car Unemployed drivers; shuttered motels
Re-design welfare state &/or job retraining.
Online/mobile education and vocational training. Apple Smartphone Access to
information 24/7. BYOD. Tele-work.
Short battery life. Problems of social disengagement.
Apple Watch. Research into better batteries.
6.1 Individual researcher i.d.’s (ORCID)
Advances in information technology facilitated international collaborative virtual research teams and wider access to scientific journals. This, plus the general globalization that is also enabled by new IT, raises research capacity in developing nations. In turn, many more researchers from many more countries produce work publishable in top international journals. Distinguishing among researchers having similar surnames (or names inconsistently transliterated into Western alphabets), never much of a problem heretofore, became an issue and an entrepreneurial opportunity. The universal researcher identifier was invented and promulgated. Publishing companies’ author and reviewer databases now need to be modified to carry the extra data field “universal author identifier.” The earlier cozy research communities where (as in
Cheers) everybody knows your name, morphs into a more impersonal but perhaps
more productive enterprise.
In this example, summarized in Table 3, technical change led to new ways to use technology, which led to new organizational forms. These in turn created demand for new technological solutions. These newer solutions, once provided, led to still newer usage modalities and a new round of social change in research communities. The wheel takes another turn.
Table 3. Example: Individual researcher i.d.’s and the Circle of Innovation Each event … … turns the wheel.
Advances in ICT Technological innovation E-journals; Collaboration platforms New products/services More submissions from more countries to premier
journals New ways to use products & services More international co-authorships. More authors with
similar surnames. New social/professional interactions Online conferences; Global research teams; Bigger
research communities. New ways to organize Need to uniquely identify researchers with similar
names New needs & problems
ORCID and other identifier systems Technological innovation; new product/service Add fields to existing databases, to accommodate
researcher i.d. number New ways to organize
6.2 “Your Phone Is Ruining Your Life: The Real Reason Apple Developed the iWatch”
Apple’s iPad and iPhone changed the way we work. Now a revolutionary wristwatch may extend Apple’s dominant product line. Apple understands most iPhone users are bothered by the buzz of the smartphone and the constant checking of messages. The phones have become invasive. Technology distracts us from the things we should pay the most attention to—family or friends, or something meaningful in our lives. To filter out useless messages and save the important ones, Apple introduced functions in the iWatch to make a different and better quality of life (Pierce, 2015; see also Maxcer, 2015).
Pierce asks, “Can technology fix a socio-psychological problem it created with another piece of technology?” The iWatch uses your level of interest in the information, as demonstrated by your reaction to it, as a cue for the iWatch to prioritize, to get your face out of your tech. Apple introduced a feature called Short Look: An induced pulse on the wrist signals an incoming text message. The duration of the screen display depends on how long you cock your wrist and look at the watch.
Time will tell whether the iWatch truly reflects Circle of Innovation thinking. So far, bloggers are offering preliminary evidence that it does.5 CEO Tim Cook has said Apple puts a “maniacal” focus on making “not good products, or a lot of products, but the absolute best products in the world.”6 It appears that anticipating possible psychological, social, and organizational consequences of a product is part of what can place it, and its successor products, among the “absolute best products in the world.”
We can expect to see more of this from Apple, and to see other companies follow suit.7
5 E.g., the Oatmeal blog, http://theoatmeal.com/blog/apple_watch
6 http://www.thelowdownblog.com/2015/06/should-apple-get-rid-of-mac.html#more
7 The examples up to this footnote marker are provided by the International Association for Impact Assessment, http://iaia.org/iaiawiki/techassess.ashx.
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7
The Circle of Innovation: Implications
The Circle of Innovation is a simple idea. But it… 1. Introduces a new classification of innovations.
2. Gives a new view of targetmarketing.
3. Has implications for sustainable product line planning.
4. Should change how we report the prospective impact of innovation.
7.1 Classifying innovations and defining innovation
The Circle of Innovation suggests a new classification of innovations. Traditionally we classify innovations as Continuous, Discontinuous, or Radical. Now we must add a classifier: Innovations that provide old benefits in a cheaper, more efficient, or more enjoyable way, versus those providing new, unprecedented benefits.
Lab-driven innovations (if we exclude those of a “solution looking for a problem” nature) are meant to improve an existing situation. However, the Circle of Innovation shows that such an innovation can, via social and organizational change, lead to new and possibly unprecedented problems. The latter will be addressed by a second kind of innovation, i.e., one that provides benefits that had never been sought before.
Following ideas of Ijiri and Simon (Ijiri 1990), Philips (2001, 2011) defined innovation in terms of the experience curve: “Innovation is a non-differentiable point in an experience curve.” This remains vacuously true for innovations that deliver new, unprecedented benefits, as the start of production represents the beginning point of the learning curve.
7.2 The Circle of Innovation and target marketing
Conventional segmentation targets customers’ demographic or psychographic characteristics. Echoing Ted Levitt’s 1983 dictum, “Customers don’t need quarter-inch drills, they need quarter-inch holes,” Clayton Christensen (of “disruptive innovation” fame) said in 2003, target products to the customers’ “circumstances,” or usage scenarios, not to their demographics.
The Circle of Innovation goes beyond Levitt and Christensen; it says, The product will
change the circumstances. Because innovative products change organizations and
create new needs, marketers face an analog of quantum uncertainty: When the product is launched at the target market, the target moves.
As a result, companies must plan products that are robust to changed circumstances. They must anticipate the possible new circumstances and plan follow-on products to fit them. Prior literature hints at this, but does not follow the reasoning far enough to reach the above conclusion. Examples include the ideas of sociological expectations (Berkhout, 2006), and empathic design (Leonard and Rayport, 1997). The idea of scenario-based design (Bødker, 2000 and Carroll, 2000) comes closest, and indeed scenario exercises may be the most fruitful way to plan product lines in the framework of the Circle of Innovation.
Gover (2015) offers an example of how the product changes the circumstances – though in this example the change was unanticipated. Again, ICT was the driver,
enabling the creation of MOOCs. MOOCs were intended to allow any university to economize in offering courses. In an unexpected turn, MOOCs created the media superstar professor, attracting students to tele-study at a progressively smaller number of non-local universities, and then the creation of new training organizations like Coursera and Khan Academy, and even in-house streaming corporate training programs. These things happened in parallel with (and in response to) a growing need for coders and engineers, and rising costs of traditional university education.
Gover remarks that the “linear model [of innovation] is still used in the USA R&D community.” Because the product changes the circumstances, it is clear that business people as well as researchers will have to begin thinking in nonlinear fashion.
7.3 Assessing technology and planning sustainable product lines
“Industrial TA” (Daim et al 2011) is Technology Assessment performed by companies. Companies appear to direct most of their assessment activities to the capabilities they aim to procure, rather than to those they aim to sell. A further implication of the Circle of Innovation is that firms should assess the technologies they intend to release to the market – not just the technologies they wish to procure – and that they should do this for potential profit. By anticipating the new needs that today’s innovation will generate, the innovative company may jump-start the development of further products to meet those needs, bringing the further products to market before competitors can do so. This results in sustainable product lines.
This will not be easy. Side-effects and created problems/needs are likely to be both delayed and systemic, even as firms rush to meet their market windows. The shrinking life span of corporations (Daepp et al, 2015, report the average company lifespan has dropped from 67 years in the 1920s to 15 years today) exacerbates “short-termism” and would seem to make long-baseline technology assessments nearly impossible. Porter et al (1991) wrote that home appliance maker Whirlpool Corporation succeeded in this in one project and failed in another. Whirlpool tracked other companies’ work on permanent-press fabrics in order to design permanent press cycles for washers and dryers, “beating their competition to market by about a year [and achieving a] substantial gain in market share.” In contrast, “Whirlpool introduced the trash compactor without adequate impact assessment.” Compacted trash proved not easily biodegradable in landfills, and was perceived to be a “hazard to municipal incinerators.” The company introduced new models that mitigated the problems, but these were not very successful in the marketplace.
The Circle of Innovation implies a product planning process similar to that urged by the Responsible Innovation and Sustainable Innovation movements. However, the latter tend to focus on one product at a time. (See e.g., Sutcliffe, 2011) The future-oriented technology assessment demanded by the Circle of Innovation implies the planning of product lines.
Figure 2 assembles the implications of the Circle of Innovation into a rough diagrammatic outline for product line planning in an environmentally delicate, highly regulated, and litigious world. The Figure is intentionally simplistic, for the sake of its rhetorical point. Nonetheless, while ten years ago such a diagram would be dismissed as hopelessly idealistic, it contains no ideas that today’s managers cannot easily accept.
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In the Figure, technology assessment is commenced before product launch, with foreseeable social/organizational changes, and their consequent new demands, anticipated to the extent possible. Positive and negative consequences are honestly noted, and classified as to whether they are within the firm’s control, and as to whether they affect only buyer and seller or are systemic, creating externalities.
The firm examines whether tweaks to the product spec, or other measures the company may take, will change these consequences for the better. Failing that, are there follow-on products that can profitably ameliorate negative effects of the present product? (Our earlier example showed that Apple is doing this, though they commenced doing so long after the launch of the iPhone.)
The alternative to killing a potentially profitable product (due to excessive negative side-effects) is to find a niche market for which the side-effects are minimally important. Statin drugs, for example, while evidently not a good fit for the mass market, may benefit people who are known to be at high risk for heart disease and at low risk for (or are too elderly to worry about the future onset of) cancer or diabetes.
Though marketers would not recommend it, every firm’s motto could be “Solving today’s problems, and creating tomorrow’s!” For this reason, innovators must consider and decide whether the problem they’re solving is worse than the problems they’re creating. Needless to say, ethical companies will not deliberately create problems simply in order to market solutions to them.
